Charting the trajectory of cognitive diagnostic assessment in language assessment: A systematic literature review

Abstract

The education system has relied on conventional single-score assessments, which provide limited insights into students' cognitive abilities. Cognitive diagnostic assessment (CDA) offers a promising alternative by providing detailed information on students' cognitive processes. The review aims to explore the recent trends of cognitive diagnostic assessment publications in language assessment by examining the years of publications, geographical locations, research methodologies, focused skills, and research samples. It further investigates the implementation of CDA studies in language assessment and identifies proposed future research directions in this field. Findings show a surge in CDA studies since 2019, with China and Iran leading, predominantly focusing on receptive skills and retrofitting methods over true CDA. The review shows that CDA accentuates cognitive model design, Q-matrix construction, item development, comparison of cognitive diagnostic models (CDMs), data analysis, and mastery profile generation. Previous research has proposed recommendations related to item and instrument development, attribute selection, sample selection, and the effectiveness of CDA. The study limitations include potential biases from publication trends and the reliance on existing literature, possibly excluding unpublished works. Future efforts should focus on developing comprehensive cognitive models, balancing the assessment of receptive and productive skills, and expanding the analysis of item parameters. The review's findings imply that practitioners must align existing tests with diagnostic needs and incorporate various item parameters to enhance assessment accuracy. It also underscores the implication that educational policymakers should support refined cognitive models and that teachers must be trained to use advanced diagnostic tools for effective instructional strategies.

Keywords

• Cognitive diagnostic assessment
• Cognitive diagnostic models
• Classification diagnostic models
• Language assessment
• Systematic literature review

References

1. Akbay, L. (2021). Impact of retrofitting and item ordering on DIF. Journal of Measurement and Evaluation in Education and Psychology, 12(2), 212 225. https://doi.org/10.21031/epod.886920
2. Alallo, H.M.I., Mohammed, A., Hamid, Z.K., Hassan, A.Y., & Kadhim, Q.K. (2023). Examining attribute relationship using Diagnostic Classification Models: A mini review. International Journal of Language Testing, 13 (Special Issue), 21 30. https://doi.org/10.22034/IJLT.2022.368468.1212
3. Alavi, M., & Ranjbaran, F. (2018). Constructing and validating a Q-Matrix for cognitive diagnostic analysis of a reading comprehension test battery. Journal of English Language Teaching and Learning, 21(12), 1 15. https://elt.tabrizu.ac.ir/article_17207_d9a9150ba8996ecfe90af3e07b905503.pdf
4. Aryadoust, V. (2011). Application of the fusion model to while-listening performance tests. JALT Testing & Evaluation SIG Newsletter, 15(2), 2–9.
5. Aryadoust, V. (2018). A cognitive diagnostics assessment study of the listening test of the Singapore–Cambridge General Certificate of Education O-Level: Application of DINA, DINO, G-DINA, HO-DINA, and RRUM. International Journal of Listening, 35(1), 29-52. https://doi.org/10.1080/10904018.2018.1500915
6. Askari, M., & Karami, H. (2024). On the relationship between sensory learning styles and reading subskill profiles: An application of Fusion Model. Language Related Research, 15(3), 245–274. https://doi.org/https://doi.org/10.29252/LRR.15.3.10
7. Boori, A.A., Ghazanfari, M., Ghonsooly, B., & Baghaei, P. (2023). The construction and validation of a Q-matrix for cognitive diagnostic analysis: The case of the reading comprehension section of the IAUEPT. International Journal of Language Testing, 13(Special Issue), 31–53. https://doi.org/10.22034/IJLT.2023.383112.1227
8. Boori, A.A., Ghazanfari, M., Ghonsooly, B., & Baghaei, P. (2024). A cognitive diagnostic modeling analysis of the reading comprehension section of an Iranian high-stakes language proficiency test. International Journal of Language Testing, 14(1), 17 33. https://doi.org/10.22034/IJLT.2023.399561.1256

9. Chen, H., Cai, Y., & de la Torre, J. (2023). Investigating second language (L2) reading subskill associations: A cognitive diagnosis approach. Language Assessment Quarterly, 20(2), 166–189. https://doi.org/https://doi.org/10.1080/15434303.2022.2140050
10. Chen, H., & Chen, J. (2015). Exploring reading comprehension skill relationships through the G DINA model. Educational Psychology, 36(6), 1049 1064. https://doi.org/10.1080/01443410.2015.1076764
11. Chen, H., & Chen, J. (2016). Retrofitting non-cognitive-diagnostic reading assessment under the Generalized DINA Model framework. Language Assessment Quarterly, 13(3), 218–230. https://doi.org/10.1080/15434303.2016.1210610
12. Doe, C. (2014). Diagnostic English Language Needs Assessment (DELNA). Language Testing, 31(4), 537–543. https://doi.org/10.1177/0265532214538225
13. Dong, Y., Ma, X., Wang, C., & Gao, X. (2021). An optimal choice of cognitive diagnostic model for second language listening comprehension test. Frontiers in Psychology, 12, 1–12. https://doi.org/10.3389/fpsyg.2021.608320
14. Du, W., & Ma, X. (2021). Probing what’s behind the test score: application of multi-CDM to diagnose EFL learners’ reading performance. Reading and Writing, 34(6), 1441–1466. https://doi.org/10.1007/s11145-021-10124-x
15. Embretson, S. (1984). A general latent trait model for response process. Psychometrika, 49(2), 175–186.
16. Fan, T., Song, J., & Guan, Z. (2021). Integrating diagnostic assessment into curriculum: a theoretical framework and teaching practices. Language Testing in Asia, 11(2), 1–23. https://doi.org/10.1186/s40468-020-00117-y
17. Fan, T., & Yan, X. (2020). Diagnosing English reading ability in Chinese senior high schools. Studies in Educational Evaluation, 67, 1 12. https://doi.org/10.1016/j.stueduc.2020.100931
18. Fischer, G.H., & Formann, A.K. (1982). Some applications of logistic latent trait models with linear constraints on the parameters. Applied Psychological Measurement, 6(4), 397–416. https://doi.org/10.1177/014662168200600403
19. Geramipour, M., Talebzadeh, H., & Mahdi, S. (2021). The optimal Cognitive Diagnostic Model (CDM) for the Grammar Section of MA Entrance Examination of State Universities for EFL candidates. Language Related Research, 12(1), 187 218. https://doi.org/10.29252/LRR.12.1.6
20. Gierl, M.J., & Cui, Y. (2008). Defining characteristics of diagnostic classification models and the problem of retrofitting in cognitive diagnostic assessment. Measurement: Interdisciplinary Research & Perspective, 6(4), 263 268. https://doi.org/10.1080/15366360802497762
21. Ha, H.T. (2021). Exploring the relationships between various dimensions of receptive vocabulary knowledge and L2 listening and reading comprehension. Language Testing in Asia, 11(1), 1–20. https://doi.org/10.1186/s40468-021-00131-8
22. He, L., Jiang, Z., & Min, S. (2021). Diagnosing writing ability using China’s Standards of English Language Ability: Application of cognitive diagnosis models. Assessing Writing, 50, 1–14. https://doi.org/10.1016/j.asw.2021.100565
23. Hemati, S.J., & Baghaei, P. (2020). A cognitive diagnostic modeling analysis of the English reading comprehension section of the Iranian National University Entrance Examination. International Journal of Language Testing, 10(1), 11 32. https://www.ijlt.ir/article_114278_022ab6b64d4bc8acba9c561846828270.pdf
24. Hong, Q.N., Pluye, P., Fàbregues, S., Bartlett, G., Boardman, F., Cargo, M., Dagenais, P., Gagnon, M., Griffiths, F., Nicolau, B., O’Cathain, A., Rousseau, M.-C., & Vedel, I. (2018). Mixed Methods Appraisal Tool (MMAT) version 2018: User guide. McGill Department of Family Medicine.
25. Huang, Q., & Bolt, D.M. (2023). Relative robustness of CDMs and (M)IRT in measuring growth in latent skills. Educational and Psychological Measurement, 83(4), 808–830. https://doi.org/10.1177/00131644221117194
26. Ishak, H., Matore, M.E.E.M., & Nor, H.A.M. (2025). Bibliometric analysis of adaptive behavior research: Advancing Sustainable Development Goals (SDGs) for children with disabilities. Journal of Lifestyle and SDG’s Review, 5(2), 1 25. https://doi.org/10.47172/2965-730X.SDGsReview.v5.n02.pe03405
27. Jang, E.E. (2009a). Cognitive diagnostic assessment of L2 reading comprehension ability: Validity arguments for Fusion Model application to LanguEdge assessment. Language Testing, 26(1), 31–73. https://doi.org/10.1177/0265532208097336
28. Jang, E.E. (2009b). Demystifying a Q-Matrix for making diagnostic inferences about L2 reading skills. Language Assessment Quarterly, 6(3), 210 238. https://doi.org/10.1080/15434300903071817
29. Jang, E.E., Dunlop, M., Park, G., & Boom, E.H. Van Der. (2015). How do young students with different profiles of reading skill mastery, perceived ability, and goal orientation respond to holistic diagnostic feedback? Language Testing, 32(3), 1 25. https://doi.org/10.1177/0265532215570924
30. Javidanmehr, Z., Reza, M., & Sarab, A. (2019). Retrofitting non-diagnostic reading comprehension assessment: Application of the G-DINA Model to a high-stakes reading comprehension test. Language Assessment Quarterly, 16(3), 1 18. https://doi.org/10.1080/15434303.2019.1654479
31. Javidanmehr, Z., & Sarab, M.R.A. (2017). Cognitive diagnostic assessment: Issues and considerations. International Journal of Language Testing, 7(2), 73 98. https://www.ijlt.ir/article_114441_feee78c9ca19261a6b44843ca71cd075.pdf
32. Ketabi, S., Alavi, S.M., & Ravand, H. (2021). Diagnostic test construction: Insights from cognitive diagnostic modeling. International Journal of Language Testing, 11(1), 22–35. https://www.ijlt.ir/article_128357_68e74c779145d7be54c24f610a549879.pdf
33. Kim, A.Y. (2015). Exploring ways to provide diagnostic feedback with an ESL placement test: Cognitive diagnostic assessment of L2 reading ability. Language Testing, 32(2), 227–258. https://doi.org/10.1177/0265532214558457
34. Lee, K. (2023). Diagnosing Chinese college-level English as a Foreign Language (EFL) learners’ integrated writing capability: A Log-linear Cognitive Diagnostic Modeling (LCDM) study. Assessing Writing, 57, 1–13. https://doi.org/10.1016/j.asw.2023.100730
35. Lee, S., Lee, T., Liu, R., Joo, S., Shi, D., Lee, S., & Lee, T. (2025). Research trends and challenges in diagnostic classification models: Insights from dynamic topic modeling. Measurement: Interdisciplinary Research and Perspectives, 1 32. https://doi.org/10.1080/15366367.2025.2493998
36. Lee, Y.-W., & Sawaki, Y. (2009a). Application of three cognitive diagnosis models to ESL reading and listening assessments. Language Assessment Quarterly, 6(3), 239–263. https://doi.org/10.1080/15434300903079562
37. Lee, Y.-W., & Sawaki, Y. (2009b). Cognitive diagnosis approaches to language assessment: An overview. Language Assessment Quarterly, 6(3), 172 189. https://doi.org/10.1080/15434300902985108
38. Leighton, J.P., & Gierl, M.J. (2007a). Cognitive Diagnostic Assessment for Education (1st ed.). Cambridge University Press.
39. Leighton, J.P., & Gierl, M.J. (2007b). Defining and evaluating models of cognition used in educational measurement to make inferences about examinees’ thinking processes. Educational Measurement: Issues and Practice, 26(2), 3 16. https://doi.org/10.1111/j.1745-3992.2007.00090.x
40. Li, H., Hunter, C.V., & Lei, P.-W. (2015). The selection of cognitive diagnostic models for a reading comprehension test. Language Testing, 33(3), 391 409. https://doi.org/10.1177/0265532215590848
41. Li, H., & Suen, H.K. (2013). Constructing and validating a Q-matrix for cognitive diagnostic analyses of a reading test. Educational Assessment, 18(1), 1 25. https://doi.org/10.1080/10627197.2013.761522
42. Li, L., An, Y., Ren, J., & Wei, X. (2021). Research on the cognitive diagnosis of Chinese listening comprehension ability based on the G-DINA Model. Frontiers in Psychology, 12, 1–15. https://doi.org/10.3389/fpsyg.2021.714568
43. Li, S., & Wang, J. (2017). Diagnostic assessment of L2 Chinese learners’ reading comprehension ability. In D. Zhang & C. Lin (Eds.), Chinese as A Second Language Assessment (pp. 183–202). Springer.
44. Li, Y., Huang, C., & Liu, J. (2023). Diagnosing primary students’ reading progression: Is cognitive diagnostic computerized adaptive testing the way forward? Journal of Educational and Behavioral Statistics, 48(6), 842 865. https://doi.org/10.3102/10769986231160668
45. Li, Y., Zhen, M., & Liu, J. (2021). Validating a reading assessment within the cognitive diagnostic assessment framework: Q-matrix construction and model comparisons for different primary grades. Frontiers in Psychology, 12, 1 13. https://doi.org/10.3389/fpsyg.2021.786612
46. Liang, L., Lu, J., Zhang, J., & Shi, N. (2022). Modeling not-reached items in cognitive diagnostic assessments. Frontiers in Psychology, 13, 1 16. https://doi.org/10.3389/fpsyg.2022.889673
47. Lim, Y.S., & Bangeranye, C. (2024). The choice between cognitive diagnosis and item response theory: A case study from medical education. International Journal of Testing, 24, 356–389. https://doi.org/10.1080/15305058.2024.2369561
48. Liu, R., Huggins-Manley, A.C., & Bulut, O. (2018). Retrofitting Diagnostic Classification Models to responses from IRT-based assessment forms. Educational and Psychological Measurement, 78(3), 357–383. https://doi.org/10.1177/0013164416685599
49. Lockwood, C., Munn, Z., & Porritt, K. (2015). Qualitative research synthesis: Methodological guidance for systematic reviewers utilizing meta-aggregation. International Journal of Evidence Based Healthcare, 13(3), 179 187. https://doi.org/10.1097/XEB.0000000000000062
50. Ma, W., Minchen, N., & de la Torre, J. (2020). Choosing between CDM and Unidimensional IRT: The proportional reasoning test case. Measurement: Interdisciplinary Research and Perspectives, 18(2), 87–96. https://doi.org/10.1080/15366367.2019.1697122
51. Mei, H., & Chen, H. (2022). Cognitive diagnosis in language assessment: A thematic review. RELC Journal, 55(2), 1–9. https://doi.org/10.1177/00336882221122357
52. Meng, Y., & Fu, H. (2023). Modeling mediation in the dynamic assessment of listening ability from the cognitive diagnostic perspective. Modern Language Journal, 107, 137 160. https://doi.org/10.1111/modl.12820
53. Meng, Y., Wang, Y., & Zhao, N. (2023). Cognitive diagnostic assessment of EFL learners’ listening barriers through incorrect responses. Frontiers in Psychology, 14, 1 11. https://doi.org/10.3389/fpsyg.2023.1126106
54. Min, S., Cai, H., & He, L. (2022). Application of Bi-factor MIRT and Higher-order CDM Models to an in-house EFL listening test for diagnostic purposes. Language Assessment Quarterly, 19(2), 189–213. https://doi.org/10.1080/15434303.2021.1980571
55. Min, S., & He, L. (2022). Developing individualized feedback for listening assessment: Combining standard setting and cognitive diagnostic assessment approaches. Language Testing, 39(1), 90–116. https://doi.org/10.1177/0265532221995475
56. Mirzaei, A., Vincheh, M.H., & Hashemian, M. (2020). Retrofitting the IELTS reading section with a general cognitive diagnostic model in an Iranian EAP context. Studies in Educational Evaluation, 64, 1–10. https://doi.org/10.1016/j.stueduc.2019.100817
57. Mohamed Shaffril, H.A., Abu Samah, A., Samsuddin, S.F., Ahmad, N., Tangang, F., Ahmad Sidique, S.F., Abdul Rahman, H., Burhan, N.A.S., Arif Shah, J., & Amiera Khalid, N. (2024). Diversification of agriculture practices as a response to climate change impacts among farmers in low-income countries: A systematic literature review. Climate Services, 35, 1–18. https://doi.org/10.1016/j.cliser.2024.100508
58. Mohamed Shaffril, H.A., Samsuddin, S.F., & Abu Samah, A. (2021). The ABC of systematic literature review: The basic methodological guidance for beginners. Quality and Quantity, 55(4), 1319–1346. https://doi.org/10.1007/s11135-020-01059-6
59. Mohammed, A., Kareem, A., Dawood, S., Alghazali, T., Khlaif, Q., Sabti, A.A., & Sabit, S.H. (2023). A cognitive diagnostic assessment study of the Reading Comprehension Section of the Preliminary English Test (PET). International Journal of Language Testing, 13, 1-20. https://www.ijlt.ir/article_159609_0730ddc075382ca20884ce32b794c85f.pdf
60. Mohd Noh, M.F., & Mohd Matore, M.E.E. (2020). Rating performance among raters of different experience through multi-facet Rasch measurement (MFRM) model. Journal of Measurement and Evaluation in Education and Psychology, 11(2), 147 162. https://doi.org/10.21031/epod.662964
61. Mohd Noh, M.F., & Mohd Matore, M.E.E. (2022). Rater severity differences in English language as a second language speaking assessment based on rating experience, training experience, and teaching experience through many-faceted Rasch measurement analysis. Frontiers in Psychology, 13, 1–13. https://doi.org/10.3389/fpsyg.2022.941084
62. Mohd Noh, M.F., & Mohd Matore, M.E.E. (2024). Conundrum and considerations in Cognitive Diagnostic Assessment for language proficiency evaluation. Information Management and Business Review, 16(2), 63–72. https://doi.org/10.22610/imbr.v16i2(I).3690
63. Mohd Noh, M.F., Mohd Matore, M.E.E., & Sulaiman, N.A. (2025). A cross-age odyssey of cognitive reading attributes: A scoping review. Frontiers in Psychology, 16, 1 19. https://doi.org/10.3389/fpsyg.2025.1605898
64. Musid, N.A., Matore, M.E.E.M., & Hamid, A.H.A. (2024). A scoping review on mapping the digital leadership constructs for educational settings: what we can learn? International Journal of Evaluation and Research in Education, 13(1), 111 121. https://doi.org/10.11591/ijere.v13i1.26760
65. Nadmilail, A.I., Mohd Matore, M.E.E., Maat, S.M., & Sheridan, L. (2023). Broad vs. narrow traits: A scoping review of measuring personality traits in teacher selection using the situational judgment test. Frontiers in Psychology, 14, 1 15. https://doi.org/10.3389/fpsyg.2023.1217321
66. Nájera, P., Sorrel, M.A., de la Torre, J., & Abad, F.J. (2020). Improving robustness in Q-matrix validation using an iterative and dynamic procedure. Applied Psychological Measurement, 44(6), 431–446. https://doi.org/10.1177/0146621620909904
67. Nallasamy, R., & Khairani, A.Z. (2022). Validating reading comprehension assessment under the GDINA Model. Malaysian Journal of Social Sciences and Humanities (MJSSH), 7(11), 1–12. https://doi.org/10.47405/mjssh.v7i11.1877
68. Panahi, A., & Mohebbi, H. (2022). Cognitive diagnostic assessment of IELTS Listening: Providing feedback from its internal structure. Language Teaching Research Quarterly, 29, 147–160. https://doi.org/10.32038/ltrq.2022.29.10
69. Parums, D.V. (2021). Editorial: Review articles, systematic reviews, meta-analysis, and the updated preferred reporting items for systematic reviews and meta-analyses (PRISMA) 2020 Guidelines. Medical Science Monitor, 27, 1 3. https://doi.org/10.12659/MSM.934475
70. Poolsawad, K., Kanjanawasee, S., & Wudthayagorn, J. (2015). Development of an English communicative competence diagnostic approach. Procedia - Social and Behavioral Sciences, 191, 759–763. https://doi.org/10.1016/j.sbspro.2015.04.462
71. Puente, A., Alvarado, J.M., Gutierrez de Blume, A., & Calderón Maureira, J.F. (2023). An application of cognitive diagnostic models in the evaluation of reading comprehension in Chilean university students. Suma Psicológica, 30(1), 40 47. https://doi.org/10.14349/sumapsi.2023.v30.n1.5
72. Ranjbaran, F., & Alavi, S.M. (2017). Developing a reading comprehension test for cognitive diagnostic assessment: A RUM analysis. Studies in Educational Evaluation, 55, 167–179. https://doi.org/10.1016/j.stueduc.2017.10.007
73. Ravand, H. (2016). Application of a Cognitive Diagnostic Model to a high-stakes reading comprehension test. Journal of Psychoeducational Assessment, 34(8), 782 799. https://doi.org/10.1177/0734282915623053
74. Ravand, H., & Baghaei, P. (2019). Diagnostic classification models: Recent developments, practical issues, and prospects. International Journal of Testing, 20(1), 24 56. https://doi.org/10.1080/15305058.2019.1588278
75. Ravand, H., & Robitzsch, A. (2018). Cognitive diagnostic model of best choice: A study of reading comprehension. Educational Psychology, 38(10), 1255 1277. https://doi.org/10.1080/01443410.2018.1489524
76. Rupp, A.A., Templin, J., & Henson, R.A. (2010). Diagnostic Measurement: Theory, Methods, and Applications. The Guilford Press.
77. Sabtu, S.H., & Mohd Matore, M.E.E. (2024). Systematic literature review on the implementation of the Six Sigma approach in education. International Journal of Evaluation and Research in Education, 13(1), 262 270. https://doi.org/10.11591/ijere.v13i1.26196
78. Safari, F., & Ahmadi, A. (2023). Developing and evaluating an empirically-based diagnostic checklist for assessing second language integrated writing. Journal of Second Language Writing, 60, 1–15. https://doi.org/10.1016/j.jslw.2023.101007
79. Sakaria, D., Maat, S.M., & Mohd Matore, M.E.E. (2023). Factors influencing mathematics teachers’ pedagogical content knowledge (PCK): A systematic review. Pegem Eğitim ve Öğretim Dergisi, 13(2), 1–14. https://doi.org/10.47750/pegegog.13.02.01
80. Sawaki, Y., Kim, H., & Gentile, C. (2009). Q-Matrix construction: Defining the link between constructs and test items in large-scale reading and listening comprehension assessments. Language Assessment Quarterly, 6(3), 190 209. https://doi.org/10.1080/15434300902801917
81. Seipel, B., Kennedy, P.C., Carlson, S.E., Clinton-Lisell, V., & Davison, M.L. (2023). MOCCA-College: Preliminary validity evidence of a cognitive diagnostic reading comprehension assessment. Journal of Learning Disabilities, 56(1), 58 71. https://doi.org/10.1177/00222194221121340
82. Sessoms, J., & Henson, R.A. (2018). Applications of diagnostic classification models: A literature review and critical commentary. Measurement: Interdisciplinary Research and Perspectives, 16(1), 1–17. https://doi.org/10.1080/15366367.2018.1435104
83. Shahmirzadi, N. (2023). Validation of a language center placement test: Differential item functioning. International Journal of Language Testing, 13(1), 1 17. https://doi.org/10.22034/IJLT.2022.336779.1151
84. Shahmirzadi, N., & Marashi, H. (2023). Cognitive diagnostic assessment of reading comprehension for high- stakes tests: Using GDINA model. Language Testing in Focus: An International Journal, 8(8), 1–16. https://doi.org/10.32038/ltf.2023.08.01
85. Shahsavar, Z. (2019). Diagnosing English learners’ writing skills: A cognitive diagnostic modeling study. Cogent Education, 6(1), 1 19. https://doi.org/10.1080/2331186X.2019.1608007
86. Shan, N., & Wang, X. (2020). Cognitive diagnosis modeling incorporating item-level missing data mechanism. Frontiers in Psychology, 11, 1 11. https://doi.org/10.3389/fpsyg.2020.564707
87. Shi, X., Ma, X., Du, W., & Gao, X. (2024). Diagnosing Chinese EFL learners’ writing ability using polytomous cognitive diagnostic models. Language Testing, 41(1), 109 134. https://doi.org/10.1177/02655322231162840
88. Sohrabi, C., Franchi, T., Mathew, G., Kerwan, A., Nicola, M., Griffin, M., Agha, M., & Agha, R. (2021). PRISMA 2020 statement: What’s new and the importance of reporting guidelines. International Journal of Surgery, 88, 39 42. https://doi.org/10.1016/j.ijsu.2021.105918
89. Sun, H., & Hwang, Y. (2023). Enhancing EFL learners’ English reading performance through the diagnostic feedback of CDA. Korean Journal of English Language and Linguistics, 23, 535–553. https://doi.org/10.15738/kjell.23..202307.535
90. Svetina, D., Gorin, J.S., & Kikumi, K. (2011). Defining and comparing the reading comprehension construct: A cognitive-psychometric modeling approach. International Journal of Testing, 11(1), 1–23. https://doi.org/10.1080/15305058.2010.518261
91. Syed Ismail, S.A., Maat, S.M., & Khalid, F. (2024). 35 years of fraction learning: Integrating systematic review and bibliometric analysis on a global scale. Eurasia Journal of Mathematics, Science and Technology Education, 20(12), 1 19. https://doi.org/10.29333/ejmste/15657
92. Tabatabaee-Yazdi, M. (2020). Hierarchical diagnostic classification modeling of reading comprehension. SAGE Open, 10(2), 1–13. https://doi.org/10.1177/2158244020931068
93. Tatsuoka, K.K. (1983). Rule Space: An approach for dealing with misconceptions based on Item Response Theory. Journal of Educational Measurement, 20(4), 345–354.
94. Tatsuoka, K.K. (1990). Toward an integration of item-response theory and cognitive error diagnosis. In Fredericksen, Glaser, Lesgold, & Shafto (Eds.), Diagnostic Monitoring of Skill and Knowledge Acquisition (pp. 453–488). Routledge.
95. Thi, D.T.D., & Loye, N. (2019). Cognitive diagnostic analyses of the Progress in International Reading Literacy Study (PIRLS) 2011 results. Mesure et Évaluation En Éducation, 42, 127–166. https://doi.org/10.7202/1084131ar
96. Thompson, W.J., & Clark, A.K. (2024). Improving instructional decision-making using Diagnostic Classification Models. Educational Measurement: Issues and Practice, 43(4), 146–156. https://doi.org/https://doi.org/10.1111/emip.12619
97. Tonekaboni, F.R., Ravand, H., & Rezvani, R. (2021). The construction and validation of a Q-matrix for a high-stakes reading comprehension test : A G-DINA study. International Journal of Language Testing, 11(1), 58 87. https://www.ijlt.ir/article_128361_4488710c7301b77e88a7aca333162624.pdf
98. Toprak-yildiz, T.E. (2021). An international comparison using cognitive diagnostic assessment: Fourth graders’ diagnostic profile of reading skills on PIRLS 2016. Studies in Educational Evaluation, 70, 1–10. https://doi.org/10.1016/j.stueduc.2021.101057
99. Toprak-Yildiz, T.E. (2022). Developing a cognitive model of L2 reading comprehension for evaluative purposes in an EMI context. Studies in Educational Evaluation, 75, 1 11. https://doi.org/10.1016/j.stueduc.2022.101200
100. Toprak, T.E., & Cakir, A. (2021). Examining the L2 reading comprehension ability of adult ELLs: Developing a diagnostic test within the cognitive diagnostic assessment framework. Language Testing, 38(1), 106 131. https://doi.org/10.1177/0265532220941470
101. van der Linden, W.J. (2016). Handbook of Item Response Theory, Volume 1. CRC Press.
102. von Davier, M., & Lee, Y.-S. (2019). Handbook of Diagnostic Classification Models. Springer.
103. Wang, C., & Lu, J. (2021). Learning attribute hierarchies from data: Two exploratory approaches. Journal of Educational and Behavioral Statistics, 46(1), 58 84. https://doi.org/10.3102/1076998620931094
104. Wang, X., Zhang, Q., & Gu, L. (2024). A comparative study on cognitive diagnostic assessment of EFL listening in a Chinese College English Context. Social Science Research Network (SSRN), 1–25.
105. Xie, Q. (2016). Diagnosing university students’ academic writing in English: Is cognitive diagnostic modelling the way forward? Educational Psychology, 37(1), 1 22. https://doi.org/10.1080/01443410.2016.1202900
106. Yi, Y. (2016). Probing the relative importance of different attributes in L2 reading and listening comprehension items: An application of cognitive diagnostic models. Language Testing, 34(3), 1–9. https://doi.org/10.1177/0265532216646141
107. Yi, Y. (2017). In search of optimal cognitive diagnostic model(s) for ESL grammar test data – Findings from a model comparison study. Applied Measurement in Education, 30(2), 82–101. https://doi.org/10.1080/08957347.2017.1283314
108. Yumsek, M. (2023). Educational L2 constructs and diagnostic measurement. Language Testing in Asia, 13(1), 1–23. https://doi.org/10.1186/s40468-022-00214-0
109. Zhang, H., Wu, X., & Ju, M. (2024). Developing a cognitive model of solid geometry based on Interpretive Structural Modeling method. Heliyon, 10(5), 1 12. https://doi.org/10.1016/j.heliyon.2024.e27063
110. Zhang, X., & Wang, J. (2020). On the sequential hierarchical cognitive diagnostic model. Frontiers in Psychology, 11, 1–13. https://doi.org/10.3389/fpsyg.2020.579018
111. Zhao, H., Wang, W., & Huang, Y. (2020). A cognitive analysis of an English reading test through the G DINA model. Journal of Physics: Conference Series, 1, 1 7. https://doi.org/10.1088/1742-6596/1629/1/012037